JP7040376B2 - Data collection system and vehicle - Google Patents

Description

The present invention relates to a data acquisition technique using a vehicle.

In recent years, with the spread of vehicles connected to networks (connected cars), a system for collecting data using a moving vehicle has been studied. By collecting the data acquired by the moving vehicle, for example, it is expected to be applied to enable automatic generation of road map data.
As a technique related to this, for example, Patent Document 1 discloses a system in which a center collects images taken by a mobile terminal and generates map data.

Japanese Unexamined Patent Publication No. 2005-241715 Japanese Unexamined Patent Publication No. 2014-228673

When the center collects data (for example, images) acquired by a vehicle, there arises a problem that the amount of data becomes excessive depending on the traffic volume. For example, duplicate data may be transmitted from an area through which many vehicles pass, which may occupy network resources. In addition, there may be a problem that information is not transmitted from an area where there are few passing vehicles.

The present invention has been made in consideration of the above problems, and an object of the present invention is to optimize data collection in a system for collecting data acquired by a vehicle.

The data collection system according to the present invention is
It is a data collection system consisting of a server device, one or more data acquisition vehicles, and the server device collects the data acquired by the data acquisition vehicle, and the server device is a plurality of data collection systems for which data should be collected. It is a map showing a unit area, and has a transmission means for transmitting a map including the passing traffic volume of the data acquisition vehicle for each unit area to the data acquisition vehicle, and the data acquisition vehicle is the unit area. In any of these, the acquisition means for acquiring the data and the control means for transmitting the acquired data to the server device based on the map received from the server device, and the control means is the unit. It is characterized in that, among the acquired data, the data to be transmitted to the server device is determined based on the passing traffic volume for each area.

Further, the vehicle according to another aspect of the present invention is
A vehicle that acquires data and transmits the acquired data to a server device, and is a map showing a plurality of unit areas for which data should be collected, including the passing traffic volume of the vehicle for each unit area. It has a receiving means for receiving a map, an acquisition means for acquiring the data in any one of the unit areas, and a control means for transmitting the acquired data to the server device based on the received map. However, the control means is characterized in that, among the acquired data, the data to be transmitted to the server device is determined based on the passing traffic volume for each unit area.

Another aspect of the present invention is a program for causing a computer to execute the vehicle control method, or a computer-readable storage medium in which the program is stored non-temporarily.

According to the present invention, data collection can be optimized in a system that collects data acquired by a vehicle.

It is a schematic diagram of the data collection system which concerns on this invention. It is a block diagram of the vehicle 10 which concerns on 1st Embodiment. It is a figure explaining the block table which concerns on 1st Embodiment. It is a figure which shows the specific example of the partition table. It is a block diagram of the server apparatus 20 which concerns on 1st Embodiment. It is a schematic diagram of an image storage. It is a figure which shows the example of the data stored in an image database. It is a flowchart of the process which sends and receives a partition table. It is a flowchart of the process performed by a vehicle 10. It is a flowchart explaining the process performed in step S22. It is a figure which shows the probability that image data can be collected. It is a flowchart explaining the process performed in step S25.

The data collection system according to the present invention is a system in which a server device collects data acquired by a plurality of vehicles traveling on a road. The data may be image data, sensor data, or the like as long as it can be acquired by the vehicle. The vehicle has a function of acquiring data while traveling and transmitting the acquired data to the server device.

In such a system, depending on the amount of traffic passing through, a large amount of duplicated data may be transmitted to the server device, which may put pressure on network resources.
Therefore, in the data collection system according to the present invention, the server device is a map showing a plurality of unit areas for which data should be collected, and the map including the passing traffic volume of the data acquisition vehicle for each unit area is used as a vehicle. Send. Further, the vehicle determines the data to be transmitted to the server device among the acquired data based on the passing traffic volume described in the map.

According to this configuration, for example, for a unit area with a large amount of passing traffic, it is expected that data will be transmitted by another vehicle, so the priority of data transmission will be lowered, and for a unit area with a small amount of passing traffic, for example. Since the probability that data is transmitted by another vehicle is low, it is possible to take measures such as raising the priority of data transmission. As a result, the priority of data transmission can be made different for each unit area, and data collection can be optimized.

Further, the control means calculates the probability that the server device can collect a predetermined number of the data within a predetermined period based on the passing traffic volume for each unit area, and based on the probability, the server. It may be characterized by determining the data to be transmitted to the device.
Further, the control means may be characterized in that the data corresponding to the unit region having a lower probability is transmitted to the server device with higher priority.

As described above, when the data acquisition vehicle has the acquired data in the unit region where the probability that a predetermined number of data can be collected within a predetermined period is low, it is preferable to preferentially transmit the data. On the contrary, when the data acquisition vehicle has the data acquired in the unit area where the probability that a predetermined number of data can be collected within the predetermined period is high, the transmission priority of the data is lowered. With such a configuration, the server device can collect an appropriate number of data for each unit area.

Further, the map may be characterized in that the passing traffic volume per unit time of the data acquisition vehicle and the predetermined number are represented for each unit area.
By including the passing traffic volume per unit time and the number of data to be collected by the server device in the map, it becomes possible to calculate the probability on the vehicle side.

Further, when the amount of the data not transmitted to the server device exceeds the first threshold value, the data acquisition vehicle preferentially deletes the data corresponding to the unit region having a higher probability. It may be characterized by that.

In this way, when the remaining storage capacity of the vehicle becomes low, the data having a high probability of being transmitted by another vehicle may be preferentially deleted.

Further, the map is characterized in that the deadline time for completing the collection of the data is related to the unit area, and the control means corrects the passing traffic volume by using the deadline time. May be good. With such a configuration, it becomes possible to collect data in consideration of the deadline.

Hereinafter, specific embodiments of the present invention will be described with reference to the drawings. Unless otherwise specified, the hardware configuration, module configuration, functional configuration, etc. described in each embodiment are not intended to limit the technical scope of the invention to those alone.

(First embodiment)
FIG. 1 shows an outline of the configuration of the data collection system according to the first embodiment. The data collection system according to the present embodiment includes a plurality of vehicles 10 and a server device 20. The server device 20 is a device that manages a plurality of vehicles 10 under its control. The vehicle 10 is a connected car (data collection vehicle) capable of communicating with the server device 20 and executing a function described later. Although one server device 20 is illustrated in FIG. 1, there may be a plurality of server devices 20. Further, the number of vehicles 10 is not limited to the illustrated number.

The vehicle 10 according to the present embodiment has a function of acquiring an image outside the vehicle using an in-vehicle camera and accumulating it as image data, and a function of transmitting the acquired image data to the server device 20. The server device 20 has a function of collecting image data acquired by the vehicle 10 and analyzing the image data to generate a road map. The transmission of image data from the vehicle 10 to the server device 20 is controlled by a map (referred to as a partition table in the embodiment) generated by the server device 20.

In the present embodiment, the image data acquired by the vehicle 10 is transmitted to the server device 20 as it is, but the present embodiment is not necessarily limited to this embodiment. For example, the vehicle 10 may convert the image data into a feature amount and transmit the feature amount to the server device 20. Further, the sensor data obtained by sensing the road may be transmitted to the server device 20. In the description of the embodiment, "image data" and "data" are equivalent.

In a system in which a server device collects data acquired by a plurality of vehicles, it is necessary to control so that an excessive amount of data is not transmitted from the vehicle 10. Without such control, duplicate data (eg, substantially the same data acquired at the same point) may be transmitted by different vehicles 10 and may overwhelm network resources. be.
Further, when the road map is generated based on the data acquired by the vehicle 10, it is necessary to control so as to collect the acquired data in the target area without bias. This is because if such control is not performed, a large amount of data will be collected from an area with a large amount of traffic, but data will not be collected from an area with a small amount of traffic.

In the data collection system according to the first embodiment, in order to solve such a problem, the server device 20 distributes a map (compartment table) for instructing the vehicle 10 to collect data in the target area to the vehicle 10. The vehicle 10 determines the image data to be transmitted to the server device 20 based on the information described in the received division table.

In the data collection system according to the present embodiment, the vehicle 10 and the server device 20 are connected to each other by a network. As the network, for example, WAN (Wide Area Network), which is a global public communication network such as the Internet, or other communication networks may be adopted. Further, the network may include a telephone communication network such as a mobile phone and a wireless communication network such as Wi-Fi (registered trademark).

Next, the configuration of the vehicle 10 will be described. FIG. 2 is a diagram showing a system configuration of the vehicle 10. The vehicle 10 includes a control unit 101, a storage unit 102, a communication unit 103, an in-vehicle camera 104, and a position information acquisition unit 105.

The control unit 101 is an arithmetic unit that controls a function of acquiring and managing image data and a function of transmitting the acquired image data among the functions of the vehicle 10. The control unit 101 can be realized by an arithmetic processing unit such as a CPU (Central Processing Unit).
The control unit 101 includes three functional modules of a partition table acquisition unit 1011, a data management unit 1012, and a transmission management unit 1013. Each functional module may be realized by executing a program stored in the storage unit 102, which will be described later, by the CPU.

The partition table acquisition unit 1011 acquires a partition table from the server device 20.
Here, the division table transmitted from the server device 20 to the vehicle 10 will be described. The partition table is a map showing a unit area in which the server device 20 needs image data.
Further, the vehicle 10 determines the image data to be transmitted to the server device 20 based on the partition table received from the server device 20. FIG. 3 is a diagram for visually explaining the division table.
The division table is a map in which the area for collecting image data is divided into unit areas, and each of the plurality of unit areas is associated with the division ID, the last update time, the unit time traffic volume, and the required number of samples. .. The unit area can be defined by, for example, a 100 m square mesh, but this is not the case.

The partition ID is an identifier for uniquely identifying the unit area.
The unit time traffic volume is the passing traffic volume of the vehicle 10 (that is, the vehicle for acquiring image data) expected per unit time in the corresponding unit area. A large unit time traffic volume means that the unit area is an area where image data is likely to be collected.
The required number of samples is the remaining number of image data required by the server device 20 in the corresponding unit area. The required number of samples may vary depending on the collection status of image data at the time when the partition table is generated.

The partition table transmitted to the vehicle 10 is generated based on the master partition table stored in the server device 20. The master partition table is a partition table that includes all the unit areas targeted by the system. The server device 20 according to the present embodiment generates a partition table (a subset of the master partition table) used by the target vehicle 10 from the master partition table in order to reduce the data capacity. For example, a division table including only an area that can be reached by a certain vehicle 10 within a predetermined time is generated, and the division table is transmitted to the vehicle 10. FIG. 4 is an example of a division table generated by the server device 20 and transmitted to the vehicle 10.
The specific usage of the parcel table will be described later.

The data management unit 1012 acquires image data and manages the acquired image data. Specifically, a process of acquiring an image outside the vehicle via the vehicle-mounted camera 104 and storing it in the storage unit 102 and a process of deleting the image data stored in the storage unit 102 are performed at a predetermined cycle.
The transmission management unit 1013 performs a process of extracting the image data stored in the storage unit 102 and transmitting the image data to the server device 20 based on the received partition table.
The detailed method will be described later.

The storage unit 102 includes a main storage device and an auxiliary storage device. The main storage device is a memory in which a program executed by the control unit 101 and data used by the control program are expanded. The auxiliary storage device is a device that stores a program executed by the control unit 101 and data used by the control program. Auxiliary storage may store an operating system for running programs. The program stored in the auxiliary storage device is loaded into the main storage device and executed by the control unit 101 to realize the above-mentioned functions.

Further, the storage unit 102 temporarily stores the image data acquired by the data management unit 1012 described above. Hereinafter, the area of the storage unit 102 in which the image data is stored is referred to as an image storage.

The communication unit 103 is a wireless communication interface for connecting the vehicle 10 to the network. The communication unit 103 provides access to the network via, for example, a wireless LAN or a mobile communication service such as 3G or LTE.
The in-vehicle camera 104 is a camera capable of capturing an image of the outside of the vehicle 10. The in-vehicle camera may be installed at any position as long as it can capture the road on which the vehicle 10 is traveling.
The position information acquisition unit 105 is a means for acquiring the position information of the vehicle 10. The position information acquisition unit 105 is configured to include, for example, a GPS module, and acquires the position information (for example, latitude and longitude) of the vehicle 10.

The configuration shown in FIG. 2 is an example, and all or part of the illustrated functions may be executed by using a circuit designed exclusively for the present invention. Further, the program may be stored or executed by a combination of a main storage device and an auxiliary storage device other than those shown in the figure.

Next, the configuration of the server device 20 will be described.
FIG. 5 is a diagram showing a system configuration of the server device 20. The server device 20 includes a communication unit 201, a storage unit 202, and a control unit 203.

The server device 20 is composed of a general computer. That is, the server device 20 is a computer having a processor such as a CPU or GPU, a main storage device such as RAM or ROM, and an auxiliary storage device such as EPROM, a hard disk drive, or removable media. The removable media may be, for example, a USB memory or a disc recording medium such as a CD or DVD. An operating system (OS), various programs, various tables, etc. are stored in the auxiliary storage device, and the programs stored there are loaded into the work area of the main storage device and executed, and each component, etc. is executed through the execution of the program. By controlling the above, it is possible to realize each function that meets a predetermined purpose, as will be described later. However, some or all of the functions may be realized by hardware circuits such as ASICs and FPGAs. The server device 20 may be configured by a single computer or may be configured by a plurality of computers that cooperate with each other.

The communication unit 201 is a communication interface for connecting the server device 20 to the network. The communication unit 201 includes, for example, a network interface board and a wireless communication circuit for wireless communication.

The storage unit 202 includes a main storage device and an auxiliary storage device. The main storage device is a memory in which a program executed by the control unit 203 and data used by the control program are expanded. The auxiliary storage device is a device that stores a program executed by the control unit 203 and data used by the control program. Since the main storage device and the auxiliary storage device are the same as those of the storage unit 102, detailed description thereof will be omitted.

Further, the storage unit 202 stores the image database 202A and the partition table database 202B.
The image database 202A is a database that stores image data collected from the vehicle 10. The image database 202A is built in the image storage described above. In the following description, "accumulating image data in the image storage" means adding image data to the image database 202A.
The division table database 202B is a database that stores a master division table for generating a division table to be distributed to the vehicle 10.

These databases are constructed by a database management system (DBMS) program executed by a processor that manages data stored in a storage device. The database used in this embodiment is, for example, a relational database.

The control unit 203 is an arithmetic unit that controls the control performed by the server device 20. The control unit 203 can be realized by an arithmetic processing unit such as a CPU.
The control unit 203 includes two functional modules, an image management unit 2031 and a partition table management unit 2032. Each functional module may be realized by executing the program stored in the auxiliary storage means by the CPU.

The image management unit 2031 collects image data from a plurality of vehicles 10 and manages them by the image database 202A.
The division table management unit 2032 generates and transmits a division table to be distributed to a plurality of vehicles 10 based on the master division table stored in the division table database 202B.
The specific processing will be described later.

Next, the outline of the process in which the vehicle 10 collects the image data will be described.
FIG. 6 is a diagram showing an image storage in the storage unit 102. Image data acquired by the data management unit 1012 is sequentially added to the image storage. The image data in the image storage is deleted at the timing of being transmitted to the server device 20 or at a predetermined timing for organizing the image data.

Three types of standard values (low-water mark, middle-water mark, and high-water mark) regarding the amount of data are set in the image storage.
The low watermark (M _LOW ) is a reference value for determining whether or not to transmit image data to the server device 20. If the amount of image data is less than the low watermark, the image data is not transmitted because the image data is not sufficiently accumulated.
The high watermark (M _HIGH ) is a reference value for determining that the capacity of the image storage is tight. When the amount of image data exceeds the high watermark, the image data is deleted until it falls below the middle watermark ( _MMID ).
Each watermark may be set at system startup or at the factory.

While traveling, the vehicle 10 (data management unit 1012) periodically acquires image data via the vehicle-mounted camera and sequentially adds the image data to the acquisition buffer in the storage unit 102. As shown in FIG. 7, the image data is associated with the section ID and the data acquisition time. The partition ID can be specified based on the partition table received from the server device 20 and the location information acquired by the location information acquisition unit 105.
The image data added to the acquisition buffer is moved to the image storage by a process described later.

Before explaining the process of transmitting the image data stored in the image storage to the server device 20, the update of the partition table will be described.
The vehicle 10 periodically communicates with the server device 20 to update the division table. FIG. 8 is a flowchart of the partition table update process. The process shown in FIG. 8 may be executed at predetermined intervals while the vehicle 10 is running, or may be executed every time a predetermined event occurs. For example, it may be executed every time the ignition of the vehicle 10 is turned ON.

First, in step S11, the vehicle 10 (partition table acquisition unit 1011) transmits a request for the division table to the server device 20 (partition table management unit 2032). Request The request contains the following information:
(1) Position information of the vehicle 10 (2) Of the image data stored in the image storage, a list of section IDs corresponding to the image data that has not been transmitted to the server device 20 (hereinafter referred to as a list of untransmitted sections).
(3) Scheduled travel route of the vehicle 10 Of these, the position information of the vehicle 10 can be acquired from the position information acquisition unit 105. Further, the planned travel route of the vehicle 10 may be acquired from a navigation device provided in the vehicle or a terminal possessed by the occupant. It is not essential to transmit the untransmitted section list and the planned travel route.

Next, in step S12, the server device 20 (partition table management unit 2032) extracts the range to be transmitted to the vehicle 10 from the master division table based on the received request request, and generates the division table.
As shown in FIG. 4, the generated parcel table includes the parcel ID, the last update time, the unit time traffic volume, and the required number of samples.
It is preferable that the division table transmitted to the vehicle 10 includes only the range that the vehicle 10 can reach within a predetermined time (for example, until the next update timing of the division table). Such a range can be estimated based on, for example, the position information of the vehicle 10 and the planned travel route.
Further, when transmitting / receiving a list of untransmitted sections, the section ID included in the list may be extracted and added.

Next, in step S13, the server device 20 (division table management unit 2032) transmits the generated division table to the vehicle 10. The division table transmitted to the vehicle 10 is temporarily stored.

Next, in step S14, the vehicle 10 (data management unit 1012) refers to the stored division table and deletes the image data that does not need to be transmitted to the server device 20 from the image storage. The image data that does not need to be transmitted to the server device 20 is, for example, as follows.
(1) This is because the image data server device 20 corresponding to the unit area in which the "required sample number" shown in the partition table is 0 has not obtained the image data.
(2) Image data whose last update time shown in the division table is later than the time when the image data was acquired Because the image data possessed by the own vehicle is older than that possessed by the server device 20. Is.

Next, a process in which the vehicle 10 that has received the division table transmits the accumulated image data to the server device 20 will be described. FIG. 9 is a flowchart of a process for transmitting image data performed by the vehicle 10. The process shown in FIG. 9 is executed by the transmission management unit 1013 at predetermined intervals while the vehicle 10 is traveling.

First, in step S21, it is determined whether or not the number of image data stored in the image storage exceeds the low watermark (M _LOW ). Here, if the number of accumulated image data does not exceed the low watermark, it is assumed that a sufficient amount of data has not been accumulated, and the image data is not transmitted. When the number of accumulated image data exceeds the low watermark, the process proceeds to step S22 and the image data is transmitted.

Here, the details of the process executed in step S22 will be described with reference to FIG.
First, in step S221, it is determined whether or not all of the following conditions are satisfied.
(1) There is untransmitted image data in the image storage (2) There is a margin in the maximum number of simultaneous transmissions The maximum number of simultaneous transmissions is defined for the vehicle 10. The maximum number of simultaneous transmissions represents the maximum number of image data that can be transmitted simultaneously. The transmission management unit 1013 controls so that the number of image data being transmitted at the same time does not exceed the maximum number of simultaneous transmissions. The maximum number of simultaneous transmissions may be set at system startup or at the factory.
If a negative determination is made in step S221, the image data is not transmitted and step S22 ends.

If an affirmative determination is made in step S221, the process proceeds to step S222 to generate a list of partition IDs that are candidates for transmission. Specifically, the partition IDs for which the required number of samples described in the partition table is 1 or more and the image data is not being transmitted to the server device 20 are extracted and listed. Whether or not the image data is being transmitted can be determined by the transmitting flag associated with the image data.

Next, in step S223, one section ID to be transmitted is determined from the generated list. In this step, the lot ID that is estimated to be the most difficult to collect is selected based on the "required number of samples" and the "unit time traffic volume" associated with the lot ID.

Here, based on the Poisson distribution, when the required number of samples k and the unit time traffic volume μ are given, the probability that the traffic volume exceeds k within the unit time (that is, the probability that k image data can be collected). A function that returns is defined as PoissonSF (k, μ).
FIG. 11 is a graph illustrating the output of the function. In the graph shown in FIG. 11, the horizontal axis represents the required number of samples, and the vertical axis represents the probability that image data for the required number of samples can be collected within a unit time. For example, when μ = 2 and the required number of samples is 2.
It can be seen that image data can be collected with a probability of about 60% within a unit time.

In the present embodiment, in step S223, the above-mentioned function is applied to all the partition IDs, and the partition ID having the lowest probability is determined as the transmission target. In other words, the image data that is the rarest for the server device 20 is determined as the transmission target.

When the section ID for transmission is determined, transmission of the corresponding image data is started in step S224. The transmission of the image data is performed asynchronously with the process shown in FIG. For example, the addition to the transmission queue and the actual transmission may be performed separately.
When transmission is started, 1 is added to the variable representing the number of image data being transmitted (hereinafter referred to as the number of samples being transmitted), 1 is subtracted from the required number of samples of the corresponding partition ID, and the data is related to the corresponding image data. After setting the attached transmission flag (for example, "1" is set), data transmission to the server device 20 is started. The number of samples being transmitted is a variable for comparing with the maximum number of simultaneous transmissions in step S221.

Step S225 is a step of performing processing according to the transmission result. In this step, when the image data is successfully transmitted, the transmitted image data is deleted from the image storage. Further, when the transmission of the image data fails, 1 is subtracted from the number of samples being transmitted, and 1 is added to the required number of samples of the corresponding section ID. In addition, the set transmission flag is deleted (for example, "0" is set). This step is also executed asynchronously with other steps.

The explanation will be continued by returning to FIG.
In step S23, new image data is read from the acquisition buffer and stored in the image storage.

In step S24, it is determined whether or not the number of image data stored in the image storage exceeds the high watermark (M _HIGH ). Here, if the number of accumulated image data does not exceed the high watermark, the process returns to step S21. When the number of accumulated image data exceeds the high watermark, the process proceeds to step S25 to organize the image data.

Here, the details of the process executed in step S25 will be described with reference to FIG.
First, in step S251, it is determined whether or not the number of accumulated image data exceeds the middle watermark ( _MMID ). When the number of accumulated image data is less than the middle watermark, it is considered that the image arrangement is completed, and the process of step S25 is terminated.
When the number of accumulated image data exceeds the middle watermark, in step S252, one section ID of the image data to be deleted is determined.

In step S252, the section ID that is estimated to be the easiest to collect image data is selected and targeted for deletion based on the "required sample number" and the "unit time traffic volume" associated with the section ID. .. Specifically, the above-mentioned function PoissonSF is applied to all the partition IDs, and the partition ID having the highest probability is determined as the deletion target. In other words, the image data that is easiest to collect for the server device 20 is determined as the deletion target.
In step S253, the image data corresponding to the determined section ID is deleted.

As described above, according to the first embodiment, in the system in which the vehicle 10 collects the image data and transmits it to the server device 20, the section ID for which it is difficult to collect the image data is preferentially selected and dealt with. Image data (highly rare image data) can be transmitted.
That is, it is possible to solve the problems of the prior art such that the image data is not transmitted from the unit area with a small traffic volume and the duplicate image data is transmitted from the unit area with a large traffic volume. Further, when the vehicle 10 organizes the image storage, the section ID to be deleted is determined according to the difficulty of collecting the image data. This makes it possible to prevent the highly rare image data from being deleted.

(Second embodiment)
In the first embodiment, the image data to be transmitted by the vehicle 10 to the server device 20 is selected based on both the unit time traffic volume and the required number of samples. On the other hand, the second embodiment is an embodiment in which a deadline time for collecting image data is set.

In the second embodiment, when the server device 20 generates the partition table, the deadline time in the collection of image data is associated (reference numeral 401 in FIG. 4).
Further, in the present embodiment, when the function PoissonSF (k, μ) is applied in the processing of steps S223 and S252, μ (that is, unit time traffic volume) is multiplied by the remaining time until the deadline time.
According to such a form, the probability can be generated by using the number of vehicles predicted to pass by the deadline time. That is, it is possible to operate in consideration of the deadline time in data collection.

(Modification example)
The above embodiment is merely an example, and the present invention may be appropriately modified and implemented without departing from the gist thereof.

For example, in the description of the embodiment, an example is given in which the image itself obtained by imaging the outside of the vehicle is transmitted to the server device 20, but if the information is obtained by sensing the road environment, the server device 20 collects the information. The target does not have to be the image data itself.

Further, in the description of the embodiment, the Poisson distribution is used to calculate the probability, but other probability distributions may be used. For example, it may be an empirical distribution such as a histogram. Further, the priority when the vehicle 10 transmits data to the server device 20 may be determined in combination with the quality of the data (for example, the image quality of the image data).

Further, when the server device 20 generates the division table, the travel history of the target vehicle 10 is acquired, the unit area in which the vehicle is likely to travel is predicted, and the division table is created based on the prediction result. May be generated.

Further, in the description of the embodiment, it is assumed that the server device 20 has data on the passing traffic volume of the vehicle 10 and data on the required number of samples, but the information acquired by the server device 20 from the vehicle 10 is used. Based on this, this information may be generated.
For example, even if the vehicle 10 senses the traffic volume for each unit area and transmits it to the server device 20, and the server device 20 updates the unit time traffic volume in the master division table based on the received information. good.
Further, for example, the vehicle 10 transmits the result of sensing the road to the server device 20, the server device 20 identifies the unit area for which the road map should be updated based on the received information, and the master division table is required. The number of samples may be updated.

The processes and means described in the present disclosure can be freely combined and carried out as long as technical inconsistencies do not occur.

Further, the processing described as being performed by one device may be shared and executed by a plurality of devices. Alternatively, the process described as being performed by different devices may be performed by one device. In a computer system, it is possible to flexibly change what kind of hardware configuration (server configuration) is used to realize each function.

The present invention can also be realized by supplying a computer program having the functions described in the above embodiment to the computer, and reading and executing the program by one or more processors possessed by the computer. Such a computer program may be provided to the computer by a non-temporary computer-readable storage medium that can be connected to the computer's system bus, or may be provided to the computer via a network. The non-temporary computer-readable storage medium is, for example, an arbitrary type of disk such as a magnetic disk (floppy (registered trademark) disk, hard disk drive (HDD), etc.), an optical disk (CD-ROM, DVD disk, Blu-ray disk, etc.). Includes read-only memory (ROM), random access memory (RAM), EPROM, EEPROM, magnetic cards, flash memory, optical cards, and any type of medium suitable for storing electronic instructions.

10: Vehicle 101: Control unit 102: Storage unit 103: Communication unit 104: In-vehicle camera 105: Location information acquisition unit 20: Server device 201: Communication unit 202: Storage unit 203: Control unit

Claims (7)

A data collection system consisting of a server device, one or more data acquisition vehicles, and the server device collecting data acquired by the data acquisition vehicle.
The server device is
It is a map showing a plurality of unit areas for which data should be collected, and has a transmission means for transmitting a map including the passing traffic volume of the data acquisition vehicle for each unit area to the data acquisition vehicle.
The data acquisition vehicle is
An acquisition means for acquiring the data in any of the unit areas,
A control means for transmitting the acquired data to the server device based on the map received from the server device, and
Have,
The control means determines the data to be transmitted to the server device among the acquired data based on the passing traffic volume for each unit area.
Data collection system. The control means calculates the probability that the server device can collect a predetermined number of the data within a predetermined period based on the passing traffic volume for each unit area, and the server device is based on the probability. Decide what data to send,
The data collection system according to claim 1. The control means preferentially transmits the data corresponding to the unit region having a lower probability to the server device.
The data collection system according to claim 2. The map is a map showing the passing traffic volume per unit time of the data acquisition vehicle and the predetermined number for each unit area.
The data collection system according to claim 2 or 3. The data acquisition vehicle preferentially deletes the data corresponding to the unit region having a higher probability when the amount of the data not transmitted to the server device exceeds the first threshold value.
The data collection system according to any one of claims 2 to 4. In the map, the deadline time at which the collection of the data should be completed is associated with the unit area.
The control means corrects the passing traffic volume using the deadline time.
The data collection system according to any one of claims 1 to 5. A vehicle that acquires data and transmits the acquired data to a server device.
A receiving means for receiving a map showing a plurality of unit areas for which data should be collected, including the passing traffic volume of the vehicle for each unit area.
An acquisition means for acquiring the data in any of the unit areas,
A control means for transmitting the acquired data to the server device based on the received map, and
Have,
The control means determines the data to be transmitted to the server device among the acquired data based on the passing traffic volume for each unit area.
vehicle.

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